code: def testPolynomialDecay_PrunesCorrectly(self):
      sparsity = pruning_schedule.PolynomialDecay(
          0.2, 0.8, 100, 110, 3, 2
      )
  
      step_100 = tf.Variable(100)
      step_102 = tf.Variable(102)
      step_105 = tf.Variable(105)
      step_110 = tf.Variable(110)
      compat.initialize_variables(self)
  
      # These values were generated using tf.polynomial_decay with the same
      # params in a colab to verify.
      self.assertAllClose(0.2, self.evaluate(sparsity(step_100))[1])
      self.assertAllClose(0.4928, self.evaluate(sparsity(step_102))[1])
      self.assertAllClose(0.725, self.evaluate(sparsity(step_105))[1])
      self.assertAllClose(0.8, self.evaluate(sparsity(step_110))[1])
  
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import compat
  from tensorflow_model_optimization.python.core.quantization.keras import utils
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
label_desc: Use image node_id 2 for calling the PolynomialDecayTest obj's underlying member method code with example usage: obj.testPolynomialDecay_PrunesCorrectly() without return types